The gravitational-wave signal GW150914 was first identified on Sept 14 2015 by searches for short-duration gravitational-wave transients. These searches identify time-correlated transients in multiple detectors with minimal assumptions aboutthe signal morphology, allowing them to be sensitive to gravitational waves emitted by a wide range of sources including binary black-hole mergers. Over the observational period from September 12th to October 20th 2015, these transient searches were sensitive to binary black-hole mergers similar to GW150914 to an average distance of $\sim 600$ Mpc. In this paper, we describe the analyses that first detected GW150914 as well as the parameter estimation and waveform reconstruction techniques that initially identified GW150914 as the merger of two black holes. We find that the reconstructed waveform is consistent with the signal from a binary black-hole merger with a chirp mass of $\sim 30 \, M_\odot$ and a total mass before merger of $\sim 70 \, M_\odot$ in the detector frame.

/pdf/observing-gravitational-wave-transient-gw150914-with-minimal-3qvyv75pvd.pdf

Observing gravitational-wave transient GW150914 with minimal assumptions

A significant amount of recent research in scientific workflows aims to develop new techniques, algorithms and systems that can overcome the challenges of efficient and robust execution of ever larger workflows on increasingly complex distributed infrastructures. Since the infrastructures, systems and applications are complex, and their behavior is difficult to reproduce using physical experiments, much of this research is based on simulation. However, there exists a shortage of realistic datasets and tools that can be used for such studies. In this paper we describe a collection of tools and data that have enabled research in new techniques, algorithms, and systems for scientific workflows. These resources include: 1) execution traces of real workflow applications from which workflow and system characteristics such as resource usage and failure profiles can be extracted, 2) a synthetic workflow generator that can produce realistic synthetic workflows based on profiles extracted from execution traces, and 3) a simulator framework that can simulate the execution of synthetic workflows on realistic distributed infrastructures. This paper describes how we have used these resources to investigate new techniques for efficient and robust workflow execution, as well as to provide improvements to the Pegasus Workflow Management System or other workflow tools. Our goal in describing these resources is to share them with other researchers in the workflow research community. All of the tools and data are freely available online for the community at http://www.workflowarchive.org. These data have already been leveraged for a number of studies.

Community Resources for Enabling Research in Distributed Scientific Workflows

We consider a science network that runs applications requiring data transfers to be completed within a given deadline. The underlying network is a software defined network (SDN) that supports fine grain real-time network telemetry. Deadline-aware data transfer requests are made to a centralized network controller that schedules the flows by setting pacing rates of the deadline flows and metering the background traffic at the ingress routers. The goal of the scheduling algorithm is to maximize the number of flows that meet the deadline while maximizing the network utilization. In this paper, we develop a Reinforcement Learning (RL) agent based network controller and compare its performance with well-known heuristics. For a network consisting of a single bottleneck link, we show that the RL-agent based network controller performs as well as Earliest Deadline First (EDF), which is known to be optimal. We also show that the RL-agent performs significantly better than an idealized TCP protocol in which the bottleneck link capacity is equally shared among the competing flows. We also study the sensitivity of the RL-agent controller for different parameter settings and reward functions.

A Reinforcement Learning Based Network Scheduler for Deadline-Driven Data Transfers

Existing accounts of public-goods distribution rely on the existence of solidarity for providing non-universal public goods, such as the humanities or national parks. There are three fundamental problems with these accounts: they ignore instances of social fragmentation; they treat preferences for public goods as morally benign, and they assume that these preferences are the only relevant moral consideration. However, not all citizens unanimously require public goods such as the humanities or national parks. Public-goods distribution that is based only on citizens’ preferences, therefore, means that non-universal public good are at a constant risk of under-provision, and has negative implications for human flourishing. The paper, therefore, develops a complementary justification for the distribution of public goods, that decouples the distribution of public goods from ad hoc preferences, and grounds the distributive justification in the intrinsic value of these goods. There are three reasons to in...

Why the intrinsic value of public goods matters

In this dissertation we study gravitational-wave data analysis techniques for binary neutron star and black hole mergers. During its first observing run, the Advanced Laser Interferometer Gravitational-wave Observatory (Advanced LIGO) reported the first, direct observations of gravitational waves from two binary black hole mergers. We present the results from the search for binary black hole mergers which unambiguously detected the binary black hole mergers. We determine the effect of calibration errors on the detection statistic of the search. Since the search is not designed to precisely measure the astrophysical parameters of the binary neutron star and black hole mergers, we use Bayesian methods to develop a new parameter estimation analysis. We demonstrate the performance of the analysis on the binary black hole mergers detected during Advanced LIGO’s first observing run. We use the parameter estimation analysis to assess the ability of gravitational-wave observatories to observe a gap in the black hole mass distribution between 52 M and 133 M due to pair-instability supernovae. Finally, we use simulated signals added to the Advanced LIGO detectors to validate the search and parameter estimation analyses used to publish the detection of the astrophysical events. THE DETECTION AND PARAMETER ESTIMATION OF BINARY BLACK HOLE MERGERS

/pdf/the-detection-and-parameter-estimation-of-binary-black-hole-2ouxapz2gm.pdf

The detection and parameter estimation of binary black hole mergers

suspension control system [1] used analog circuitry to implement the closed loop damping required for local control of each the suspended optics. Recent developments in analog to digital converters (ADC), digital to analog converters (DAC), increased processor speed and performance, and the use of reflective memory have made a digital alternative possible. Such a control system would provide additional performance and flexibility that will be required for operation of the interferometers. This paper will describe the real-time digital servo control systems that have been designed, developed and implemented for the LIGO suspended optics. In addition, the paper will describe how the suspension controls have been integrated into the overall LIGO control and data acquisition systems [2].

Laser interferometer gravitational wave observatory -ligo-

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

R. Bork

Author Tools

Chat about Author

Papers

Laser interferometer gravitational wave observatory -ligo-